(1) Field
The present invention relates to signal/image processing. More specifically, the present invention relates to image compression.
(2) Background Information
Using traditional Fourier analysis transforms, any signal may be approximated as a sum of sinusoidal waveforms of assorted frequencies. While Fourier transforms are ideally suited for signals having repeated behavior, such as speech signals, Fourier transforms fail to efficiently approximate signals with sharp discontinuities such as the edge features of images, or signals encoded for digital communications.
Wavelets are used as a way to represent an image in both the frequency and spatial domain. Due to quantization effects, less visual side effects are produced when using wavelets compared to a block based discrete cosine transform (DCT). A transform, similar to the Fourier transform, Discrete Wavelet Transform (DWT), based on Wavelet analysis, has been developed to represent signals with discontinuous features. The DWT is a "discrete" algorithm, that rather than approximating a signal using continuous waveforms, approximates the signal by discrete samples of waveforms. Since the transform is discrete, the DWT may be implemented using digital logics such as Very Large Scale Integrated (VLSI) circuits. Thus DWT may be integrated on a chip with other digital components.
The essence of DWT is to decompose an input signal into two or more frequency sub-bands. An input signal may be decomposed into two outputs--a low frequency sub-band output, obtained by using a low-pass filter, and a high frequency sub-band output, obtained by using a high-pass filter. Each of these sub-bands may be encoded separately using a suitable coding system. Each sub-band may further be divided into smaller and smaller sub-bands as is required.
In general, DWT is a computationally very intensive process and hence very slow when computed using a general purpose computing system. To make it suitable for real-time applications, a special purpose custom VLSI chip may be used for DWT, exploiting the underlying data parallels to yield high throughput and hence high data rate. Several VLSI architectures for DWT have been proposed. However, most of these complex architectures require large hardware area and yield much less than 100 percent hardware utilization. It is desirable to provide a new DWT architecture for performing image compression that utilizes a reduced number of hardware parts.